Gender: Female 
Age: 60+
Nationality: United Kingdom
Ethnicity: White / Caucasian 
Marital status: Single 
First language: English 
Religion: Christian 
Education: High school or below
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 7
Home: Own 
Employment: Self-employed part time
Occupation: Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations)
Mother's occupation: Clerical support workers (those who perform clerical duties such as organizing, storing, computing and retrieving information)
Father's occupation: Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations)
Hobbies: Listen to jazz;Visit to stately homes;Exercise;Use social media;Go to museums and galleries;Other (Please specify) Theatre
Devices used daily: Laptop;Smartphone;Tablet 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Sentiment analysis (e.g. automatically detect if user reviews are positive or negative)Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Speech-to-Text (i.e. a computer transcribing your spoken language to written language) 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Sentiment analysis (e.g. automatically detect if user reviews are positive or negative)Machine translation (e.g. translate Chinese or Russian into English, and vice versa) 
NLP tools they would find useful: Text-to-Speech (i.e, computers being able to read out loud written language);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
Frequency of LLM use: Sometimes
LLMs used: ChatGPT 
LLM use cases: Brainstorming;Writing (e.g., composing emails);Generic chatbot conversation;Solving math or logical problems;Learning (e.g., explaining complex concepts in simple terms);Answering questions about general knowledge;Other (specify) Advice on family matters and illnesses
Contexts of LLM use: Learning;Personal;Creative or artistic;Work 
Prompt 1: I have enquired about helping my son with his weight problem
Prompt 2: I have enquired about supporting my son with his depression
Prompt 3: I have enquired about the basics of building an annex in the garden of a new home
Prompt 4: I have  asked about the signs of dementia
Prompt 5: I have asked about medication for depression by name eg Citalopram
Prompt 6: I have asked about ADHD medication - ritalin